Instructions to use chosenone80/bert-ner-test-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chosenone80/bert-ner-test-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chosenone80/bert-ner-test-2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chosenone80/bert-ner-test-2") model = AutoModelForTokenClassification.from_pretrained("chosenone80/bert-ner-test-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 687b013f248e27f13f54077341f2add53dab6ad00aa7d60859111540e227bfc3
- Size of remote file:
- 431 MB
- SHA256:
- 467858ea5a42ca805a42a606167adb31de9142376b0d34daa7cb68a46ce1031e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.